Process Mining in HR — The Human Factor
The topic of “automation” is often addressed at the same time as “machine manufacturing”, “robots” and “artificial intelligence”. The reason is obvious — automating means transferring responsibilities to machines. This has long been accepted in large industries such as manufacturing.
In Process Mining, this is often no different. The core industries are usually the production industry, the energy sector, e-commerce or telecommunications. In these highly digitalized fields with high data volumes, there is a lot of potential for automated process analysis.
But what if you look at an area that by definition relies on people as the core factor? What opportunities does Process Mining offer in HR departments, personnel management and recruiting?
Lana Labs has spoken to Markus Starke about this issue. As a consultant, he has mainly been active in process and organizational design since 2010 and is one of the first experts to get to the heart of personnel processes with Process Mining.
His approach: “In human resources management, there are definitely processes where Process Mining is very useful.” However, according to Mr. Starke, the analysis approach cannot necessarily be equated with the use cases from production and energy. “The realization of a Process Mining project in HR often has its own obstacles.“
What application areas does Human Resources offer for Process Mining?
Starke speaks from experience: “The most important things are usually the processing and cycle times.“
The HR sector comprises a large number of different processes. External as well as internal stakeholders are involved in recruiting, from contract drafting to master data management. Documents are created, signatures entered, data updated and correspondence documented. But the core factor “time” is always in focus. Process Mining tools such as LANA show which process step takes how long, where bottlenecks arise and where unexpectedly high waiting times occur.
Similarly, data-based process analysis can identify unexpected redundancies. Starke describes a classic example: “Document creation is a major effort driver in HR. Process loops can occur particularly quickly there. An employment contract is created several times, or a job posting is processed simultaneously by two people. In HR, it has been difficult to achieve real transparency on these processes up to now“.
The reason is obvious: “A large number of process variations occur due to individual working methods and a large spectrum of different specifications. With classical analysis methods, you can’t even get access to a lot of data and information“. Process Mining enables process managers and consultants like Markus Starke to create this transparency.
This not only helps in the proactive analysis of process performance, but also in reporting. Dashboards and data visualizations are the key to providing companies with both detailed and sustainable insight into personnel processes.
What added value does Process Mining bring to HR?
HR departments are often under a lot of pressure to be cost effective and to quickly deliver high quality results to customers who may be future, current or former colleagues. “I see reducing unnecessary labour waste as a core issue,” says Starke. “Minimizing this consumption of resources can be achieved through automation or machine learning, for example. These are also relevant topics in human resources. But the basic prerequisite for this is a lean and efficient process design.“
This is where the data-driven approach of Process Mining comes into play. The in-depth analysis of process flows identifies concretely where such optimization measures would be appropriate — and where they would not.
This demand for full process transparency applies to all types of process deviations. There are many reasons for such deviations, ranging from errors in the system to inadequate communication between those responsible. All this is difficult to record structurally in day-to-day business. Process Mining offers the necessary means to detect such problem cases. The result: more efficient systems and data-based communication.
Finally, the question of standards and guidelines in human resources is also important. Reference models should normally function as a control mechanism for correct process flows. “Such reference models do exist, and most companies have defined their own target models,” explains Starke. “The problem is to develop a model that can also be used with the data actually collected.” The conformance checking of actual and target processes is of great relevance, but is difficult to implement manually in such varied process landscapes. Process Mining offers the possibility not only to generate new, accurate reference models, but also to compare them automatically with the lived process.
Where does the technology reach its limits?
Process Mining is not a perfect panacea. HR brings some unique challenges to the use of automated process analysis. Starke names one of the most important distinguishing features: “In the production sector there are machines that either have the data — or not. In HR, this is often not so clear. So far, I have rarely seen processes that have been processed completely stringently in one or two systems.“
The system landscape in personnel management and recruiting is “fractured”, says Starke. Companies often have their own master data system, a service management tool and software for document management. In addition, there are often other specialized systems, e.g. for recruiting. The system landscape at international companies is becoming even more complex. This extreme heterogeneity of the software does not prevent the use of Process Mining solutions, but requires very flexible, open interfaces for data exchange.
“In addition, there are always relevant activities that are not stored in the systems, but take place in paper form, via e-mail or verbally,” says Markus Starke. The human factor cannot be fully equated with machines and IT systems.
The solution: Process Mining and people knowledge
Sustainable process excellence requires an effective combination of data analysis with Process Mining tools such as LANA and the expertise of experts such as consultant Markus Starke. The digital transformation of companies is opening more and more doors for profitable Process Mining projects. But even in the future, dealing with people — from applicants to employees — will rarely take place completely on the digital stage. Process Mining and classic process management in HR complement each other. This is where knowledge of people meets knowledge of data.
In just two steps, you can begin to design your business processes more effectively and to sustainably leverage savings potential.
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